Optimal Drug Regimens for TB: An Integrated Computational/Experimental Approach

结核病的最佳药物治疗方案：综合计算/实验方法

• 批准号: 8514488
• 负责人: Michael A. Lyons
• 金额: $ 12.29万
• 依托单位: COLORADO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-04 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8514488
• 关键词: Algorithms; Animal Testing; Animals; Antibiotics; Antimicrobial Resistance; Antitubercular Agents; Bayesian Analysis; Biological; Chemicals; Clinical Sciences; Clinical Trials; Colorado; Combination Drug Therapy; Combined Modality Therapy; Communicable Diseases; Complex; Computers; Computing Methodologies; Data; Development; Disease; Dose; Drug Combinations; Drug Interactions; Drug Kinetics; Drug Resistant Tuberculosis; Drug resistance; Educational workshop; Engineering; Environment; Environmental Health; Evaluation; Faculty; Focus Groups; Genus Mycobacterium; Goals; Growth; Health Sciences; Human; Immunology; In Vitro; Infection; Infectious Diseases Research; K-Series Research Career Programs; Laboratory Research; Literature; Mentors; Methodology; Methods; Microbiology; Modeling; Mus; Mycobacterium tuberculosis; Outcome; Pathology; Pharmaceutical Preparations; Pharmacodynamics; Physics; Population; Process; Public Health; Pyrazinamide; Radiologic Health; Reading; Regimen; Reporting; Research; Research Training; Review Literature; Rifampin; Risk; Science; Specific qualifier value; Staging; Testing; Time; Toxic effect; Training; Training Programs; Translations; Treatment Protocols; Tuberculosis; Universities; Veterinary Medicine; antimicrobial drug; base; career; college; computer framework; computer science; computerized tools; dosage; drug development; improved; in vivo; isoniazid; killings; mathematical model; meetings; mycobacterial; novel; pathogen; pre-clinical; preclinical evaluation; research study; skills; success; tuberculosis drugs; tuberculosis treatment

DESCRIPTION (provided by applicant): The candidate in this K25 application has a background in theoretical physics and computer science. The long term career goal of this candidate is to combine rigorous training in the field of bioscience with his quantitative and computer skills in order to accelerate the late-stage drug development process for the treatment of tuberculosis (TB). The immediate goal is to develop improved computational methods and tools to determine new optimal combination therapies for TB in the preclinical stage of development. This Career Development Award is requested to support a research and training program that includes intensive coursework, mentored readings, attendance at workshops, meetings and seminars, and a research plan that provides for a well-founded understanding of the host-drug-pathogen interactions for the treatment of TB. The candidate will be supported by the Department of Microbiology, Immunology and Pathology at Colorado State University (CSU). The mentors and collaborators for this proposal include faculty from the Mycobacteria Research Laboratories (MRL), the Department of Environmental & Radiological Health Sciences, Chemical & Biological Engineering, and the Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences. CSU is a leader in infectious disease research, and the MRL, with their 19 faculty and over 100 full-time staff, is the worlds largest group focused on mycobacterial research, providing an ideal environment to be introduced to the field of TB research, and for the success of this project. In order to provide guidance for clinical trial testing of new drug regimens for TB, there is a clear need for an efficient method to determine optimal combination regimens in the preclinical stage of development. While conventional pharmacokinetic/pharmacodynamic (PK/PD) methods have proven useful for the determination of optimal single drug antimicrobial regimens, they are data intensive and have limited utility for a systematic and thorough evaluation of the 3- and 4-drug regimens required to treat TB. The objective and goal of this research plan is therefore to develop and demonstrate the use of a computational framework which provides optimal combination drug dosage regimens for treatment of Mycobacterium tuberculosis infection in mice. The proposed framework is a novel integration of physiologically based mathematical modeling, Bayesian inference, targeted experimental studies, and a rigorous method for dose optimization. The specific aims of this proposal are to: (1) develop the computational framework for host-drug-pathogen interactions and drug dose optimization in mouse TB infection models, and (2) demonstrate the use of the computational framework for the determination of an optimal multidrug regimen in mouse TB infection models. While we seek to establish the feasibility of the proposal using current front-line anti-TB drugs (isoniazid, rifampin, pyrazinamide), the ultimate aim of this project is the application of the methodology to the newer anti-TB drugs in order to render predictions of optimal regimens for testing in clinical trials.

描述（由申请人提供）：本次K25申请的候选人具有理论物理和计算机科学背景。该候选人的长期职业目标是将生物科学领域的严格训练与他的定量和计算机技能结合起来，以加速治疗结核病（TB）的后期药物开发过程。当前的目标是开发改进的计算方法和工具，以确定临床前开发阶段结核病的新的最佳联合疗法。该职业发展奖旨在支持一项研究和培训计划，其中包括强化课程、指导阅读、参加讲习班、会议和研讨会，以及一项研究计划，为结核病治疗提供对宿主-药物-病原体相互作用的有充分根据的了解。